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International Conference of the TC Electrimacs Committee, ELECTRIMACS 2024

作者： Carrasco-González, David Sarrias-Mena, Raúl Horrillo-Quintero, Pablo Llorens-Iborra, Francisco Fernández-Ramírez, Luis M. Cadiz Spain SURET Research Group Department of Engineering in Automation Electronics and Computer Architecture and Networks ETSI Algeciras Cadiz Spain

ISBN: (纸本)9783031739200

Nowadays, hybrid AC/DC microgrids (HMG) are growing in popularity because of human needs and their benefits. They are composed of the interconnection of a DC microgrid (MG) and an AC MG, and each MG is constituted by generation, energy storage, and consumption technologies. This study develops a new control strategy for an HMG consisting of a DC MG and an AC MG interconnected through a bidirectional power converter. The AC MG is composed of AC loads, a photovoltaic (PV) generator and a battery bank. The DC MG is made up of a hydrogen system, DC loads, wind turbine (WT) and ultracapacitor (UC). The HMG is evaluated under different conditions in an experimental setup constituted by an OPAL-RT 4512 unit and a Raspberry Pi microcontroller. This experimental setup permits to execute the HMG in real time and to validate the results obtained. Finally, the control system developed for this HMG presents a satisfactory behaviour under different working conditions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Wind turbines

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Design of a Robust IEEE Compliant Floating - Point Divide and Square Root Using Iterative Approximation

Design of a Robust IEEE Compliant Floating - Point Divide an...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Carson Sager James E. Stine Electrical and Computer Engineering Department VLSI Computer Architecture Research Group Oklahoma State University Stillwater OK USA

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

In this paper, we discuss an IEEE 754 compliant normalized floating-point divide and square root unit that utilizes iterative approximation. We provide a robust architecture that allows multiple formats and all IEEE 754 rounding modes while still exhibiting high-performance. Moreover, we also adhere to the IEEE 754 2019 standard and demonstrate methods for rounding results to all five rounding modes using iterative approximation. Performance, Power, and Area estimates are determined from physical synthesis using ARM-based standard cells in a TSMC 28nm process. This paper also presents comparisons versus other implementations and demonstrates the efficient of the approach presented here.

关键词： Circuits and systems computer architecture Digital arithmetic System-on-chip Iterative methods Standards Optimization

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Design of a Robust IEEE Compliant Floating - Point Divide and Square Root Using Iterative Approximation 16

Design of a Robust IEEE Compliant Floating - Point Divide an...

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16th IEEE Latin American Symposium on Circuits and Systems, LASCAS 2025

作者： Sager, Carson Stine, James E. Oklahoma State University Vlsi Computer Architecture Research Group Electrical and Computer Engineering Department StillwaterOK74078 United States

ISBN: (纸本)9798331522124

关键词： Integrated circuit design

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Bridging the Gap Between MLOps and RLOps: An Industry 4.0 Case Study on Architectural Design Decisions in Practice

Bridging the Gap Between MLOps and RLOps: An Industry 4.0 Ca...

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22nd IEEE International Conference on Software architecture, ICSA 2025

作者： Warnett, Stephen John Zdun, Uwe University of Vienna Research Group Software Architecture Faculty of Computer Science Vienna Austria University of Vienna UniVie Doctoral School Computer Science DoCS Faculty of Computer Science Vienna Austria

ISBN: (纸本)9798331520908

In the domain of Industry 4.0 Cyber-Physical Production Systems (CPPSs), Reinforcement Learning (RL) has gained momentum as an effective strategy for training intelligent agents in digital twins. Whilst the practice of Machine Learning Operations (MLOps) has become established as a holistic approach to automating workflows in supervised and unsupervised Machine Learning (ML), the extent to which MLOps practices are applicable to RL, particularly due to major differences between ML and RL concerning model deployment and model training, are not currently well-understood. The literature on RLOps as a paradigm is scarce. We tackle this open question by conducting an exploratory, qualitative, deductive-inductive industry case study on a CPPS, performing content analysis of CPPS artefacts, such as architectural schematics and source code, and understanding their relation to 22 known Architectural Design Decisions and 86 associated decision options through classification into four distinct emergent categories. Our findings help bridge the gap between MLOps and RLOps architectures, contributing novel insights into understanding the application of MLOps to RL and providing practical insights and inspiration for further research. © 2025 IEEE.

关键词： Reinforcement learning

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Bridging the Gap Between MLOps and RLOps: An Industry 4.0 Case Study on Architectural Design Decisions in Practice

Bridging the Gap Between MLOps and RLOps: An Industry 4.0 Ca...

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Working IEEE/IFIP Conference on Software architecture

作者： Stephen John Warnett Uwe Zdun Research Group Software Architecture Faculty of Computer Science University of Vienna Vienna Austria UniVie Doctoral School Computer Science DoCS Faculty of Computer Science University of Vienna Vienna Austria

ISBN: (数字)9798331520908

ISBN: (纸本)9798331520915

关键词： Training Industries Production systems Content management Software architecture Source coding Reinforcement learning Fourth Industrial Revolution Digital twins Intelligent agents

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Exploration of Design Alternatives for Reducing Idle Time in Shor’s Algorithm: A Study on Monolithic and Distributed Quantum Systems

arXiv

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arXiv 2025年

作者： Schmidt, Moritz Kole, Abhoy Wichette, Leon Drechsler, Rolf Kirchner, Frank Mounzer, Elie Robotics Research Group University of Bremen Bremen28359 Germany Bremen28359 Germany Bremen28359 Germany Group of Computer Architecture University of Bremen Bremen28359 Germany

Shor’s algorithm is one of the most prominent quantum algorithms, yet finding efficient implementations remains an active research challenge. While many approaches focus on low-level modular arithmetic optimizations, a broader perspective can provide additional opportunities for improvement. By adopting a mid-level abstraction, we analyze the algorithm as a sequence of computational tasks, enabling systematic identification of idle time and optimization of execution flow. Building on this perspective, we first introduce an alternating design approach to minimizes idle time while preserving qubit efficiency in Shor’s algorithm. By strategically reordering tasks for simultaneous execution, we achieve a substantial reduction in overall execution time. Extending this approach to distributed implementations, we demonstrate how task rearrangement enhances execution efficiency in the presence of multiple distribution channels. Furthermore, to effectively evaluate the impact of design choices, we employ static timing analysis (STA)—a technique from classical circuit design—to analyze circuit delays while accounting for hardware-specific execution characteristics, such as measurement and reset delays in monolithic architectures and ebit generation time in distributed settings. Finally, we validate our approach by integrating modular exponentiation circuits from QRISP and constructing circuits for factoring numbers up to 64 bits. Through an extensive study across neutral atom, superconducting, and ion trap quantum computing platforms, we analyze circuit delays, highlighting trade-offs between qubit efficiency and execution time. Our findings provide a structured framework for optimizing compiled quantum circuits for Shor’s algorithm, tailored to specific hardware constraints. © 2025, CC BY.

关键词： Qubits

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VRank: Enhancing Verilog Code Generation from Large Language Models via Self-Consistency

arXiv

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arXiv 2025年

作者： Zhao, Zhuorui Qiu, Ruidi Lin, Ing-Chao Zhang, Grace Li Li, Bing Schlichtmann, Ulf Munich Germany Computer Architecture and IC Design National Cheng Kung University Taiwan Hardware for Artificial Intelligence Group Technical University of Darmstadt Germany Research Group of Digital Integrated Systems University of Siegen Germany

Large Language Models (LLMs) have demonstrated promising capabilities in generating Verilog code from module specifications. To improve the quality of such generated Verilog codes, previous methods require either time-consuming manual inspection or generation of multiple Verilog codes, from which the one with the highest quality is selected with manually designed testbenches. To enhance the generation efficiency while maintaining the quality of the generated codes, we propose VRank, an automatic framework that generates Verilog codes with LLMs. In our framework, multiple code candidates are generated with LLMs by leveraging their probabilistic nature. Afterwards, we group Verilog code candidates into clusters based on identical outputs when tested against the same testbench, which is also generated by LLMs. Clusters are ranked based on the consistency they show on testbench. To determine the best candidate, Chain-of-Thought is further applied to select the best candidate from the top-ranked clusters. By systematically analyzing diverse outputs of generated codes, VRank reduces errors and enhances the overall quality of the generated Verilog code. Experimental results on the VerilogEval-Human benchmark demonstrate a significant 10.5% average increase in functional correctness (pass@1) across multiple LLMs, demonstrating VRank’s effectiveness in improving the accuracy of automated hardware description language generation for complex design tasks. © 2025, CC BY-NC-SA.

关键词： computer hardware description languages

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Challenges and considerations of applying nature-based solutions for future mega-cities: Implications for Karachi as a Sponge City

Human Settlements and Sustainability

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Human Settlements and Sustainability 2025年第1期1卷 50-61页

作者： Lubaina Soni Asifa Iqbal Faseeha Waheed Ayesha Agha Shah Naji Akbar Green Infrastructure Research Group School of Ecosystem and Forest Sciences The University of Melbourne Australia Department of Computer and Geospatial Sciences Faculty of Engineering and Sustainable Development University of Gavle Sweden Architect and Urban Designer (Freelancer) Pakistan Department of Architecture and Interior Design College of Engineering University of Bahrain Bahrain Department of Interior Design College of Architecture Art and Design Ajman University Ajman UAE

Rapid urbanization contributes to impervious surface areas resulting in higher vulnerability to flooding and loss of green spaces. Recently, sustainable methods like nature-based solutions (NBS) are effectively being used to build resilient cities. These are practices derived from nature by emulating and regulating ecosystem services. Specifically, the adaptation of sponge city (SC) concept as part of NBS is being extensively used in growing cities to help mitigate impacts of development. This study focuses on difficulties encountered by Karachi, such as extreme weather occurrences and flooding. It examines the feasibility of implementing SC methods drawing inspiration from successfully implemented examples of China and Saudi Arabia. The outcomes indicate significance of incorporating NBS and adoption of SC elements in urban planning to provide remedies for Karachi's environmental challenges.

关键词： Urbanization Stormwater management Flood mitigation Nature-based solutions Sponge city Karachi

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On the understandability of coupling-related practices in infrastructure-as-code based deployments

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Information and Software Technology 2025年 185卷

作者： Pierre-Jean Quéval Nicole Elisabeth Hörner Evangelos Ntentos Uwe Zdun University of Vienna Faculty of Computer Science Research Group Software Architecture Vienna Austria University of Vienna Doctoral School Computer Science Vienna Austria

Infrastructure as Code (IaC) empowers software developers and operations teams to automate the deployment and management of IT infrastructure through code. This is particularly valuable for continuously released deployments such as microservices and cloud-based systems. IaC technologies offer flexibility in provisioning and deploying application architectures. However, if the structure is not well-designed, it can lead to severe issues related to coupling aspects. Unfortunately, a lack of comprehensive coupling guidelines for IaC makes ensuring adherence to best practices challenging. Leveraging IaC-based models, metrics, and source code can enhance the comprehension and implementation of coupling measures. Our objective was to investigate how developers understand information derived from system source code and compare it to formal IaC system diagrams and metrics. We conducted a controlled experiment involving a group of participants to evaluate the understandability of IaC system architecture descriptions through source code inspection and formal representations. We hypothesized that providing formal IaC system diagrams and metrics as supplementary materials would improve the understanding of IaC coupling-related practices measured by task correctness . We also expected that these supplementary resources would lead to a significant increase in task duration and that there would be a notable correlation between correctness and duration . The results suggest that including formal IaC system diagrams and metrics as supplementary materials significantly enhances the comprehension of IaC coupling-related practices, as indicated by task correctness . Moreover, providing these formal representations does not significantly prolong task duration , indicating that they do not hinder understanding. A substantial correlation between task correctness and duration is evident when formal IaC system diagrams and metrics are available.

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Detecting Environment Drift in Reinforcement Learning Using a Gaussian Process 36

Detecting Environment Drift in Reinforcement Learning Using ...

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36th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2024

作者： Fang, Zhizhou Zdun, Uwe University of Vienna Research Group Software Architecture Faculty of Computer Science Austria University of Vienna Research Group Software Architecture Faculty of Computer Science Austria

ISBN: (纸本)9798331527235

This study introduces a novel two-stage method, GPAction, for detecting environment drift in reinforcement learning settings. We first train a Gaussian process predicting the reinforcement learning agents' actions and then detect environment drifts by monitoring the mean squared error between the predicted actions of a Gaussian process action predictor and actual actions. Our proposed method is evaluated against three baselines across four environments with continuous action spaces. Results demonstrate the superior performance of GPAction in detecting environment drift. In an ablation study, by analyzing the plots and AUC values of the MSEs, we show that our method GPAction can provide more distinguishable monitoring metrics than the Gaussian process state predictor. © 2024 IEEE.

关键词： Adversarial machine learning

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